Viresh Ratnakar

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it; #35,291 of 35,345 by trust here, #17,412 by citations
• Natural Language Processing — 26 citations into it
• Evaluation & Benchmarks — 21 citations into it; #3,136 of 3,147 by trust here, #2,133 by citations

Whom Viresh Ratnakar trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Markus Freitag
2. Philipp Koehn
3. Matt Post

Who trusts Viresh Ratnakar overall

1. Tom Kocmi

Papers from Viresh Ratnakar's perspective

Ordered by how strongly the researchers Viresh Ratnakar trusts endorse each paper. Same corpus, a different order for every researcher.

1. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
2. Attention is All you Need (Neural Information Processing Systems)
3. Long Short-Term Memory
4. Language Models are Few-Shot Learners (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. ImageNet classification with deep convolutional neural networks
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. RoBERTa: A Robustly Optimized BERT Pretraining Approach (arXiv.org)

Their papers

• Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation (2021) — 534 citations
• Prompting PaLM for Translation: Assessing Strategies and Performance (2022) — 234 citations